Container file analysis using machine learning model

US11283818B2 · kind B2 · utility

Assignee

• Cylance Inc. · US

Inventors

• Xuan Zhao · Irvine, US
• Matthew Wolff · Laguna Niguel, US
• John Brock · Irvine, US
• Brian Wallace · Irvine, US
• Andy Wortman · Irvine, US
• Jian Luan · Irvine, US
• Mahdi Azarafrooz · Irvine, US
• Andrew Davis · Williston, US
• Michael Wojnowicz · Irvine, US
• Derek A. Soeder · Irvine, US
• David Beveridge · Hillsboro, US
• Yaroslav Oliinyk · Portland, US
• Ryan Permeh · Laguna Hills, US

Key dates

• Filing date: Apr 28, 2020
• Grant date: Mar 22, 2022
• Expiry date: Apr 28, 2040

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N20/10
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A system is provided for training a machine learning model to detect malicious container files. The system may include at least one processor and at least one memory. The memory may include program code which when executed by the at least one processor provides operations including: processing a container file with a trained machine learning model, wherein the trained machine learning is trained to determine a classification for the container file indicative of whether the container file includes at least one file rendering the container file malicious; and providing, as an output by the trained machine learning model, an indication of whether the container file includes the at least one file rendering the container file malicious. Related methods and articles of manufacture, including computer program products, are also disclosed.